Zobrazeno 1 - 10
of 460
pro vyhledávání: '"Stricker, Didier"'
Recent weakly-supervised methods for scene flow estimation from LiDAR point clouds are limited to explicit reasoning on object-level. These methods perform multiple iterative optimizations for each rigid object, which makes them vulnerable to cluster
Externí odkaz:
http://arxiv.org/abs/2407.02920
Publikováno v:
International Journal of Computer Vision (IJCV), pages{1--22}, published by Springer in 2024
The proposed RMS-FlowNet++ is a novel end-to-end learning-based architecture for accurate and efficient scene flow estimation that can operate on high-density point clouds. For hierarchical scene f low estimation, existing methods rely on expensive F
Externí odkaz:
http://arxiv.org/abs/2407.01129
Reconstructing texture-less surfaces poses unique challenges in computer vision, primarily due to the lack of specialized datasets that cater to the nuanced needs of depth and normals estimation in the absence of textural information. We introduce "S
Externí odkaz:
http://arxiv.org/abs/2406.15831
Autor:
Khan, Muhammad Saif Ullah, Shehzadi, Tahira, Noor, Rabeya, Stricker, Didier, Afzal, Muhammad Zeshan
Automated signature verification on bank checks is critical for fraud prevention and ensuring transaction authenticity. This task is challenging due to the coexistence of signatures with other textual and graphical elements on real-world documents. V
Externí odkaz:
http://arxiv.org/abs/2406.14370
The Situational Instructions Database (SID) addresses the need for enhanced situational awareness in artificial intelligence (AI) systems operating in dynamic environments. By integrating detailed scene graphs with dynamically generated, task-specifi
Externí odkaz:
http://arxiv.org/abs/2406.13302
Autor:
Sheikh, Talha Uddin, Shehzadi, Tahira, Hashmi, Khurram Azeem, Stricker, Didier, Afzal, Muhammad Zeshan
Document layout analysis is a key area in document research, involving techniques like text mining and visual analysis. Despite various methods developed to tackle layout analysis, a critical but frequently overlooked problem is the scarcity of label
Externí odkaz:
http://arxiv.org/abs/2406.06236
Human pose estimation is a key task in computer vision with various applications such as activity recognition and interactive systems. However, the lack of consistency in the annotated skeletons across different datasets poses challenges in developin
Externí odkaz:
http://arxiv.org/abs/2405.20084
Table detection, a pivotal task in document analysis, aims to precisely recognize and locate tables within document images. Although deep learning has shown remarkable progress in this realm, it typically requires an extensive dataset of labeled data
Externí odkaz:
http://arxiv.org/abs/2405.04971
Autor:
Sinha, Sankalp, Khan, Muhammad Saif Ullah, Sheikh, Talha Uddin, Stricker, Didier, Afzal, Muhammad Zeshan
Zero-shot learning has been extensively investigated in the broader field of visual recognition, attracting significant interest recently. However, the current work on zero-shot learning in document image classification remains scarce. The existing s
Externí odkaz:
http://arxiv.org/abs/2405.03660
Table detection within document images is a crucial task in document processing, involving the identification and localization of tables. Recent strides in deep learning have substantially improved the accuracy of this task, but it still heavily reli
Externí odkaz:
http://arxiv.org/abs/2405.00187